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Fairness-Driven Private Collaborative Machine Learning

Fairness-Driven Private Collaborative Machine Learning

29 September 2021
Dana Pessach
Tamir Tassa
E. Shmueli
    FedML
ArXivPDFHTML

Papers citing "Fairness-Driven Private Collaborative Machine Learning"

6 / 6 papers shown
Title
A cautionary tale on the cost-effectiveness of collaborative AI in
  real-world medical applications
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Francesco Cremonesi
Lucia Innocenti
Sebastien Ourselin
Vicky Goh
Michela Antonelli
Marco Lorenzi
FedML
102
0
0
09 Dec 2024
Deconstructing The Ethics of Large Language Models from Long-standing
  Issues to New-emerging Dilemmas
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas
Chengyuan Deng
Yiqun Duan
Xin Jin
Heng Chang
Yijun Tian
...
Kuofeng Gao
Sihong He
Jun Zhuang
Lu Cheng
Haohan Wang
AILaw
40
16
0
08 Jun 2024
The Pursuit of Fairness in Artificial Intelligence Models: A Survey
The Pursuit of Fairness in Artificial Intelligence Models: A Survey
Tahsin Alamgir Kheya
Mohamed Reda Bouadjenek
Sunil Aryal
28
8
0
26 Mar 2024
Cross-Institutional Transfer Learning for Educational Models:
  Implications for Model Performance, Fairness, and Equity
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity
Joshua Gardner
Renzhe Yu
Quan Nguyen
Christopher A. Brooks
René F. Kizilcec
FedML
38
14
0
01 May 2023
Achieving Model Fairness in Vertical Federated Learning
Achieving Model Fairness in Vertical Federated Learning
Changxin Liu
Zhenan Fan
Zirui Zhou
Yang Shi
J. Pei
Lingyang Chu
Yong Zhang
FedML
60
12
0
17 Sep 2021
FedFair: Training Fair Models In Cross-Silo Federated Learning
FedFair: Training Fair Models In Cross-Silo Federated Learning
Lingyang Chu
Lanjun Wang
Yanjie Dong
J. Pei
Zirui Zhou
Yong Zhang
FedML
56
40
0
13 Sep 2021
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